I'm pretty confident that you don't.
You KNOW the y value when x is 1. That's given.
Your step size is .2, and each time you do your fancy-pants calculation, it gives you an approximation for what y is when x is .2 higher than before.
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So the idea is that you have a function that looks like
y' = suchandsuch
For a given starting point, you can use that function to find out what the first derivative is at that point. The first derivative gives us slope, or rate of change. So sweet, we know what the slope of the function is at that point. Sure, the slope of the function is CHANGING, but maybe it's not changing that fast. That's where the approximation business comes in. We figure out what the slope is, assume that the slope is constant, at least for a little bit, and we see where the function would end up.

|dw:1343083148521:dw|
So here's a simple example. The top line is the actual curve where the slope is steadily increasing. The bottom line is our rough approximation where we assume that the slope stays the same.

Okay, yeah. So a SUPER simple approximation would be to say "Let's assume that the slope doesn't change at all."
And I get something like this where the slope might actually change quite a lot and I get way off:
|dw:1343083474058:dw|

Or, I could add in some steps. Basically the idea is that I occasionally stop and account for the slope changing. So instead of going the whole distance under the assumption of no slope change, I stop a little bit in and go "What's a good approximation for the slope at this point"
I use the same
y' =
function that I used before|dw:1343083628908:dw|